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This paper presents a new training method for fuzzy neural network (FNN) systems to approximate unknown nonlinear continuous functions. Fast terminal sliding mode combining the finite time convergent property of terminal attractor and exponential convergent property of linear system has faster convergence to the origin in finite time. The proposed training algorithm uses the principle of the fast...
A GA based learning algorithm is proposed in this paper for the identification of TSK models. The algorithm consists of four blocks: Partition Block, GA Block, Tuning Block and Termination Block. The Partition Block is to determine an estimated partition of input variables. The GA Block is to optimise the structure of a TSK model. The Tuning Block is to fine tune the parameters of the TSK model using...
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